Author

Saeed Omidi

SIB Swiss Institute of BioinformaticsORCID 0000-0001-7024-1625Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Saeed Omidi1 paper · Lehigh University

Biology Disciplines

Click to filter author papers

Bioinformatics· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Assay:ChIP-seq· 2 Research Focus:gene regulatory network inference· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Organism:human· 1

Frequent Co-Authors

Erik van NimwegeniD· 2 shared Severin BergeriD· 2 shared Jérémie BredaiD· 1 shared Mihaela ZavolaniD· 1 shared Mikhail Pachkov· 1 shared Mikhail V. PachkoviD· 1 shared Nicholas W. Kelley· 1 shared Phil Arnold· 1 shared

Activity by Year

2017-2019 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 24 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Erik van NimwegenORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

BioinformaticsGenome ResearchPeer-reviewedJul 1, 2019

Crunch: Integrated processing and modeling of ChIP-seq data in terms of regulatory motifs

Severin Berger, Saeed Omidi, Mikhail Pachkov…·Erik van Nimwegen

Crunch automates ChIP-seq analysis and identifies regulatory motifs, finding that TFs either use single motifs or multiple co-occurring motifs in binding peaks.

13 citations

𝕏 PostBluesky

BioinformaticsPLoS Computational BiologyPeer-reviewedJul 28, 2017

Automated Incorporation of Pairwise Dependency in Transcription Factor Binding Site Prediction Using Dinucleotide Weight Tensors

Saeed Omidi, Mihaela Zavolan, Mikhail V. Pachkov…·Erik van Nimwegen

This paper introduces a new model for transcription factor binding site prediction that accounts for pairwise dependencies between positions, outperforming existing methods on ChIP-seq and HT-SELEX data.

15 citations

ChIP-seqstatistical model

𝕏 PostBluesky